Generation of mouse ES cell lines engineered for the forced induction of transcription factors

ETV4 and ETV5 orchestrate FGF-mediated lineage specification and epiblast maturation during early mouse development

Cell fate decisions in early mammalian embryos are tightly regulated processes crucial for proper development. While FGF signalling plays key roles in early embryo patterning, its downstream effectors remain poorly understood. Our study demonstrates that the transcription factors Etv4 and Etv5 are crucial mediators of FGF signalling in cell lineage specification and maturation in mouse embryos. We show that loss of Etv5 compromises primitive endoderm formation at pre-implantation stages. Furthermore, Etv4 and Etv5 (Etv4/5) deficiency delays naïve pluripotency exit and epiblast maturation, leading to elevated NANOG and reduced OTX2 expression within the blastocyst epiblast. As a consequence of delayed pluripotency progression, Etv4/Etv5-deficient embryos exhibit anterior visceral endoderm migration defects post-implantation, a process essential for coordinated embryonic patterning and gastrulation initiation. Our results demonstrate the successive roles of these FGF signalling effectors in early lineage specification and embryonic body plan establishment, providing new insights into the molecular control of mammalian development.

ETV4 and ETV5 Orchestrate FGF-Mediated Lineage Specification and Epiblast Maturation during Early Mouse Development

Cell fate decisions in early mammalian embryos are tightly regulated processes crucial for proper development. While FGF signaling plays key roles in early embryo patterning, its downstream effectors remain poorly understood. Our study demonstrates that the transcription factors Etv4 and Etv5 are critical mediators of FGF signaling in cell lineage specification and maturation in mouse embryos. We show that loss of Etv5 compromises primitive endoderm formation at pre-implantation stages. Furthermore, Etv4/5 deficiency delays naïve pluripotency exit and epiblast maturation, leading to elevated NANOG and reduced OTX2 expression within the blastocyst epiblast. As a consequence of delayed pluripotency progression, Etv4/5 deficient embryos exhibit anterior visceral endoderm migration defects post-implantation, a process essential for coordinated embryonic patterning and gastrulation initiation. Our results demonstrate the successive roles of these FGF signaling effectors in early lineage specification and embryonic body plan establishment, providing new insights into the molecular control of mammalian development.

ZSCAN4-binding motif-TGCACAC is conserved and enriched in CA/TG microsatellites in both mouse and human genomes

The Zinc finger and SCAN domain containing 4 (ZSCAN4) protein, expressed transiently in pluripotent stem cells, gametes, and early embryos, extends telomeres, enhances genome stability, and improves karyotypes in mouse embryonic stem (mES) cells. To gain insights into the mechanism of ZSCAN4 function, we identified genome-wide binding sites of endogenous ZSCAN4 protein using ChIP-seq technology in mouse and human ES cells, where the expression of endogenous ZSCAN4 was induced by treating cells with retinoic acids or by overexpressing DUX4. We revealed that both mouse and human ZSCAN4 bind to the TGCACAC motif located in CA/TG microsatellite repeats, which are known to form unstable left-handed duplexes called Z-DNA that can induce double-strand DNA breaks and mutations. These ZSCAN4 binding sites are mostly located in intergenic and intronic regions of the genomes. By generating ZSCAN4 knockout in human ES cells, we showed that ZSCAN4 does not seem to be involved in transcriptional regulation. We also found that ectopic expression of mouse ZSCAN4 enhances the suppression of chromatin at ZSCAN4-binding sites. These results together suggest that some of the ZSCAN4 functions are mediated by binding to the error-prone regions in mouse and human genomes.

Deciphering driver regulators of cell fate decisions from single-cell transcriptomics data with CEFCON

Single-cell technologies enable the dynamic analyses of cell fate mapping. However, capturing the gene regulatory relationships and identifying the driver factors that control cell fate decisions are still challenging. We present CEFCON, a network-based framework that first uses a graph neural network with attention mechanism to infer a cell-lineage-specific gene regulatory network (GRN) from single-cell RNA-sequencing data, and then models cell fate dynamics through network control theory to identify driver regulators and the associated gene modules, revealing their critical biological processes related to cell states. Extensive benchmarking tests consistently demonstrated the superiority of CEFCON in GRN construction, driver regulator identification, and gene module identification over baseline methods. When applied to the mouse hematopoietic stem cell differentiation data, CEFCON successfully identified driver regulators for three developmental lineages, which offered useful insights into their differentiation from a network control perspective. Overall, CEFCON provides a valuable tool for studying the underlying mechanisms of cell fate decisions from single-cell RNA-seq data.

Joint sequence & chromatin neural networks characterize the differential abilities of Forkhead transcription factors to engage inaccessible chromatin

The DNA-binding activities of transcription factors (TFs) are influenced by both intrinsic sequence preferences and extrinsic interactions with cell-specific chromatin landscapes and other regulatory proteins. Disentangling the roles of these binding determinants remains challenging. For example, the FoxA subfamily of Forkhead domain (Fox) TFs are known pioneer factors that can bind to relatively inaccessible sites during development. Yet FoxA TF binding also varies across cell types, pointing to a combination of intrinsic and extrinsic forces guiding their binding. While other Forkhead domain TFs are often assumed to have pioneering abilities, how sequence and chromatin features influence the binding of related Fox TFs has not been systematically characterized. Here, we present a principled approach to compare the relative contributions of intrinsic DNA sequence preference and cell-specific chromatin environments to a TF's DNA-binding activities. We apply our approach to investigate how a selection of Fox TFs (FoxA1, FoxC1, FoxG1, FoxL2, and FoxP3) vary in their binding specificity. We over-express the selected Fox TFs in mouse embryonic stem cells, which offer a platform to contrast each TF's binding activity within the same preexisting chromatin background. By applying a convolutional neural network to interpret the Fox TF binding patterns, we evaluate how sequence and preexisting chromatin features jointly contribute to induced TF binding. We demonstrate that Fox TFs bind different DNA targets, and drive differential gene expression patterns, even when induced in identical chromatin settings. Despite the association between Forkhead domains and pioneering activities, the selected Fox TFs display a wide range of affinities for preexiting chromatin states. Using sequence and chromatin feature attribution techniques to interpret the neural network predictions, we show that differential sequence preferences combined with differential abilities to engage relatively inaccessible chromatin together explain Fox TF binding patterns at individual sites and genome-wide.

Identifying Cancer Type-Specific Transcriptional Programs through Network Analysis

Identifying cancer type-specific genes that define cell states is important to develop effective therapies for patients and methods for detection, early diagnosis, and prevention. While molecular mechanisms that drive malignancy have been identified for various cancers, the identification of cell-type defining transcription factors (TFs) that distinguish normal cells from cancer cells has not been fully elucidated. Here, we utilized a network biology framework, which assesses the fidelity of cell fate conversions, to identify cancer type-specific gene regulatory networks (GRN) for 17 types of cancer. Through an integrative analysis of a compendium of expression data, we elucidated core TFs and GRNs for multiple cancer types. Moreover, by comparing normal tissues and cells to cancer type-specific GRNs, we found that the expression of key network-influencing TFs can be utilized as a survival prognostic indicator for a diverse cohort of cancer patients. These findings offer a valuable resource for exploring cancer type-specific networks across a broad range of cancer types.

Atlas of regulated target genes of transcription factors (ART-TF) in human ES cells

Background

Transcription factors (TFs) play central roles in maintaining “stemness” of embryonic stem (ES) cells and their differentiation into several hundreds of adult cell types. The regulatory competence of TFs is routinely assessed by detecting target genes to which they bind. However, these data do not indicate which target genes are activated, repressed, or not affected by the change of TF abundance. There is a lack of large-scale studies that compare the genome binding of TFs with the expression change of target genes after manipulation of each TF.

Results

In this paper we associated human TFs with their target genes by two criteria: binding to genes, evaluated from published ChIP-seq data (n = 1868); and change of target gene expression shortly after induction of each TF in human ES cells. Lists of direction- and strength-specific regulated target genes are generated for 311 TFs (out of 351 TFs tested) with expected proportion of false positives less than or equal to 0.30, including 63 new TFs not present in four existing databases of target genes. Our lists of direction-specific targets for 152 TFs (80.0%) are larger that in the TRRUST database. In average, 30.9% of genes that respond greater than or equal to twofold to the induction of TFs are regulated targets. Regulated target genes indicate that the majority of TFs are either strong activators or strong repressors, whereas sets of genes that responded greater than or equal to twofold to the induction of TFs did not show strong asymmetry in the direction of expression change. The majority of human TFs (82.1%) regulated their target genes primarily via binding to enhancers. Repression of target genes is more often mediated by promoter-binding than activation of target genes. Enhancer-promoter loops are more abundant among strong activator and repressor TFs.

Conclusions

We developed an atlas of regulated targets of TFs (ART-TF) in human ES cells by combining data on TF binding with data on gene expression change after manipulation of individual TFs. Sets of regulated gene targets were identified with a controlled rate of false positives. This approach contributes to the understanding of biological functions of TFs and organization of gene regulatory networks. This atlas should be a valuable resource for ES cell-based regenerative medicine studies.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-022-04924-3.

Dynamic regulatory module networks for inference of cell type-specific transcriptional networks

Changes in transcriptional regulatory networks can significantly alter cell fate. To gain insight into transcriptional dynamics, several studies have profiled bulk multi-omic data sets with parallel transcriptomic and epigenomic measurements at different stages of a developmental process. However, integrating these data to infer cell type-specific regulatory networks is a major challenge. We present dynamic regulatory module networks (DRMNs), a novel approach to infer cell type-specific cis-regulatory networks and their dynamics. DRMN integrates expression, chromatin state, and accessibility to predict cis-regulators of context-specific expression, where context can be cell type, developmental stage, or time point, and uses multitask learning to capture network dynamics across linearly and hierarchically related contexts. We applied DRMNs to study regulatory network dynamics in three developmental processes, each showing different temporal relationships and measuring a different combination of regulatory genomic data sets: cellular reprogramming, liver dedifferentiation, and forward differentiation. DRMN identified known and novel regulators driving cell type-specific expression patterns, showing its broad applicability to examine dynamics of gene regulatory networks from linearly and hierarchically related multi-omic data sets.

Cell fate conversion prediction by group sparse optimization method utilizing single-cell and bulk OMICs data

Cell fate conversion by overexpressing defined factors is a powerful tool in regenerative medicine. However, identifying key factors for cell fate conversion requires laborious experimental efforts; thus, many of such conversions have not been achieved yet. Nevertheless, cell fate conversions found in many published studies were incomplete as the expression of important gene sets could not be manipulated thoroughly. Therefore, the identification of master transcription factors for complete and efficient conversion is crucial to render this technology more applicable clinically. In the past decade, systematic analyses on various single-cell and bulk OMICs data have uncovered numerous gene regulatory mechanisms, and made it possible to predict master gene regulators during cell fate conversion. By virtue of the sparse structure of master transcription factors and the group structure of their simultaneous regulatory effects on the cell fate conversion process, this study introduces a novel computational method predicting master transcription factors based on group sparse optimization technique integrating data from multi-OMICs levels, which can be applicable to both single-cell and bulk OMICs data with a high tolerance of data sparsity. When it is compared with current prediction methods by cross-referencing published and validated master transcription factors, it possesses superior performance. In short, this method facilitates fast identification of key regulators, give raise to the possibility of higher successful conversion rate and in the hope of reducing experimental cost.

Loss of Foxc1 and Foxc2 function in chondroprogenitor cells disrupts endochondral ossification

Endochondral ossification initiates the growth of the majority of the mammalian skeleton and is tightly controlled through gene regulatory networks. The forkhead box transcription factors Foxc1 and Foxc2 regulate aspects of osteoblast function in the formation of the skeleton, but their roles in chondrocytes to control endochondral ossification are less clear. Here, we demonstrate that Foxc1 expression is directly regulated by the activity of SRY (sex-determining region Y)-box 9, one of the earliest transcription factors to specify the chondrocyte lineage. Moreover, we demonstrate that elevated expression of Foxc1 promotes chondrocyte differentiation in mouse embryonic stem cells and loss of Foxc1 function inhibits chondrogenesis in vitro. Using chondrocyte-targeted deletion of Foxc1 and Foxc2 in mice, we reveal a role for these factors in chondrocyte differentiation in vivo. Loss of both Foxc1 and Foxc2 caused a general skeletal dysplasia predominantly affecting the vertebral column. The long bones of the limbs were smaller, mineralization was reduced, and organization of the growth plate was disrupted; in particular, the stacked columnar organization of the proliferative chondrocyte layer was reduced in size and cell proliferation was decreased. Differential gene expression analysis indicated disrupted expression patterns of chondrogenesis and ossification genes throughout the entire process of endochondral ossification in chondrocyte-specific Foxc1/Foxc2 KO embryos. Our results suggest that Foxc1 and Foxc2 are required for normal chondrocyte differentiation and function, as loss of both genes results in disorganization of the growth plate, reduced chondrocyte proliferation, and delays in chondrocyte hypertrophy that prevents ossification of the skeleton.

Metabolic control of DNA methylation in naive pluripotent cells

Naive epiblast and embryonic stem cells (ESCs) give rise to all cells of adults. Such developmental plasticity is associated with genome hypomethylation. Here, we show that LIF-Stat3 signaling induces genomic hypomethylation via metabolic reconfiguration. Stat3-/- ESCs show decreased α-ketoglutarate production from glutamine, leading to increased Dnmt3a and Dnmt3b expression and DNA methylation. Notably, genome methylation is dynamically controlled through modulation of α-ketoglutarate availability or Stat3 activation in mitochondria. Alpha-ketoglutarate links metabolism to the epigenome by reducing the expression of Otx2 and its targets Dnmt3a and Dnmt3b. Genetic inactivation of Otx2 or Dnmt3a and Dnmt3b results in genomic hypomethylation even in the absence of active LIF-Stat3. Stat3-/- ESCs show increased methylation at imprinting control regions and altered expression of cognate transcripts. Single-cell analyses of Stat3-/- embryos confirmed the dysregulated expression of Otx2, Dnmt3a and Dnmt3b as well as imprinted genes. Several cancers display Stat3 overactivation and abnormal DNA methylation; therefore, the molecular module that we describe might be exploited under pathological conditions.

Transcription Factor-Based Fate Specification and Forward Programming for Neural Regeneration

Traditionally, in vitro generation of donor cells for brain repair has been dominated by the application of extrinsic growth factors and morphogens. Recent advances in cell engineering strategies such as reprogramming of somatic cells into induced pluripotent stem cells and direct cell fate conversion have impressively demonstrated the feasibility to manipulate cell identities by the overexpression of cell fate-determining transcription factors. These strategies are now increasingly implemented for transcription factor-guided differentiation of neural precursors and forward programming of pluripotent stem cells toward specific neural subtypes. This review covers major achievements, pros and cons, as well as future prospects of transcription factor-based cell fate specification and the applicability of these approaches for the generation of donor cells for brain repair.

Netrin-1 promotes naive pluripotency through Neo1 and Unc5b co-regulation of Wnt and MAPK signalling

In mouse embryonic stem cells (mESCs), chemical blockade of Gsk3α/β and Mek1/2 (2i) instructs a self-renewing ground state whose endogenous inducers are unknown. Here we show that the axon guidance cue Netrin-1 promotes naive pluripotency by triggering profound signalling, transcriptomic and epigenetic changes in mESCs. Furthermore, we demonstrate that Netrin-1 can substitute for blockade of Gsk3α/β and Mek1/2 to sustain self-renewal of mESCs in combination with leukaemia inhibitory factor and regulates the formation of the mouse pluripotent blastocyst. Mechanistically, we reveal how Netrin-1 and the balance of its receptors Neo1 and Unc5B co-regulate Wnt and MAPK pathways in both mouse and human ESCs. Netrin-1 induces Fak kinase to inactivate Gsk3α/β and stabilize β-catenin while increasing the phosphatase activity of a Ppp2r2c-containing Pp2a complex to reduce Erk1/2 activity. Collectively, this work identifies Netrin-1 as a regulator of pluripotency and reveals that it mediates different effects in mESCs depending on its receptor dosage, opening perspectives for balancing self-renewal and lineage commitment.

The gene regulatory network of mESC differentiation: a benchmark for reverse engineering methods

A large body of data have accumulated that characterize the gene regulatory network of stem cells. Yet, a comprehensive and integrative understanding of this complex network is lacking. Network reverse engineering methods that use transcriptome data to derive these networks may help to uncover the topology in an unbiased way. Many methods exist that use co-expression to reconstruct networks. However, it remains unclear how these methods perform in the context of stem cell differentiation, as most systematic assessments have been made for regulatory networks of unicellular organisms. Here, we report a systematic benchmark of different reverse engineering methods against functional data. We show that network pruning is critical for reconstruction performance. We also find that performance is similar for algorithms that use different co-expression measures, i.e. mutual information or correlation. In addition, different methods yield very different network topologies, highlighting the challenge of interpreting these resulting networks as a whole.This article is part of the theme issue 'Designer human tissue: coming to a lab near you'.

Directed Differentiation of Pluripotent Stem Cells by Transcription Factors

Embryonic stem cells (ESCs) and induced pluripotent stem cells (iPSCs) have been used as promising tools for regenerative medicine, disease modeling, and drug screening. Traditional and common strategies for pluripotent stem cell (PSC) differentiation toward disease-relevant cell types depend on sequential treatment of signaling molecules identified based on knowledge of developmental biology. However, these strategies suffer from low purity, inefficiency, and time-consuming culture conditions. A growing body of recent research has shown efficient cell fate reprogramming by forced expression of single or multiple transcription factors. Here, we review transcription factor-directed differentiation methods of PSCs toward neural, muscle, liver, and pancreatic endocrine cells. Potential applications and limitations are also discussed in order to establish future directions of this technique for therapeutic purposes.

Induction of human pluripotent stem cells into kidney tissues by synthetic mRNAs encoding transcription factors

The derivation of kidney tissues from human pluripotent stem cells (hPSCs) and its application for replacement therapy in end-stage renal disease have been widely discussed. Here we report that consecutive transfections of two sets of synthetic mRNAs encoding transcription factors can induce rapid and efficient differentiation of hPSCs into kidney tissues, termed induced nephron-like organoids (iNephLOs). The first set - FIGLA, PITX2, ASCL1 and TFAP2C, differentiated hPSCs into SIX2+SALL1+ nephron progenitor cells with 92% efficiency within 2 days. Subsequently, the second set - HNF1A, GATA3, GATA1 and EMX2, differentiated these cells into PAX8+LHX1+ pretubular aggregates in another 2 days. Further culture in both 2-dimensional and 3-dimensional conditions produced iNephLOs containing cells characterized as podocytes, proximal tubules, and distal tubules in an additional 10 days. Global gene expression profiles showed similarities between iNephLOs and the human adult kidney, suggesting possible uses of iNephLOs as in vitro models for kidneys.

SOX11 promotes invasive growth and ductal carcinoma in situ progression

Here, we show that SOX11, an embryonic mammary marker that is normally silent in postnatal breast cells, is expressed in many oestrogen receptor‐negative preinvasive ductal carcinoma in situ (DCIS) lesions. Mature mammary epithelial cells engineered to express SOX11 showed alterations in progenitor cell populations, including an expanded basal‐like population with increased aldehyde dehydrogenase (ALDH) activity, and increased mammosphere‐forming capacity. DCIS.com cells engineered to express SOX11 showed increased ALDH activity, which is a feature of cancer stem cells. The CD44+/CD24–/ALDH+ cell population was increased in DCIS.com cells that expressed SOX11. Upregulating SOX11 expression in DCIS.com cells led to increased invasive growth both in vitro and when they were injected intraductally in a mouse model of DCIS that recapitulates human disease. Invasive lesions formed sooner and tumour growth was augmented in vivo, suggesting that SOX11 contributes to the progression of DCIS to invasive breast cancer. We identified potential downstream effectors of SOX11 during both microinvasive and invasive tumour growth stages, including several with established links to regulation of progenitor cell function and prenatal developmental growth. Our findings suggest that SOX11 is a potential biomarker for DCIS lesions containing cells harbouring distinct biological features that are likely to progress to invasive breast cancer. © 2017 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of Pathological Society of Great Britain and Ireland.

Assessment of engineered cells using CellNet and RNA-seq

CellNet is a computational platform designed to assess cell populations engineered by either directed differentiation of pluripotent stem cells (PSCs) or direct conversion, and to suggest specific hypotheses to improve cell fate engineering protocols. CellNet takes as input gene expression data and compares them with large data sets of normal expression profiles compiled from public sources, in regard to the extent to which cell- and tissue-specific gene regulatory networks are established. CellNet was originally designed to work with human or mouse microarray expression data for 21 cell or tissue (C/T) types. Here we describe how to apply CellNet to RNA-seq data and how to build a completely new CellNet platform applicable to, for example, other species or additional cell and tissue types. Once the raw data have been preprocessed, running CellNet takes only several minutes, whereas the time required to create a completely new CellNet is several hours.

Rapid differentiation of human pluripotent stem cells into functional neurons by mRNAs encoding transcription factors

Efficient differentiation of human pluripotent stem cells (hPSCs) into neurons is paramount for disease modeling, drug screening, and cell transplantation therapy in regenerative medicine. In this manuscript, we report the capability of five transcription factors (TFs) toward this aim: NEUROG1, NEUROG2, NEUROG3, NEUROD1, and NEUROD2. In contrast to previous methods that have shortcomings in their speed and efficiency, a cocktail of these TFs as synthetic mRNAs can differentiate hPSCs into neurons in 7 days, judged by calcium imaging and electrophysiology. They exhibit motor neuron phenotypes based on immunostaining. These results indicate the establishment of a novel method for rapid, efficient, and footprint-free differentiation of functional neurons from hPSCs.

CNOT3-Dependent mRNA Deadenylation Safeguards the Pluripotent State

Poly(A) tail length and mRNA deadenylation play important roles in gene regulation. However, how they regulate embryonic development and pluripotent cell fate is not fully understood. Here we present evidence that CNOT3-dependent mRNA deadenylation governs the pluripotent state. We show that CNOT3, a component of the Ccr4-Not deadenylase complex, is required for mouse epiblast maintenance. It is highly expressed in blastocysts and its deletion leads to peri-implantation lethality. The epiblast cells in Cnot3 deletion embryos are quickly lost during diapause and fail to outgrow in culture. Mechanistically, CNOT3 C terminus is required for its interaction with the complex and its function in embryonic stem cells (ESCs). Furthermore, Cnot3 deletion results in increases in the poly(A) tail lengths, half-lives, and steady-state levels of differentiation gene mRNAs. The half-lives of CNOT3 target mRNAs are shorter in ESCs and become longer during normal differentiation. Together, we propose that CNOT3 maintains the pluripotent state by promoting differentiation gene mRNA deadenylation and degradation, and we identify poly(A) tail-length regulation as a post-transcriptional mechanism that controls pluripotency.

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CNOT3 is required for mouse epiblast maintenance during early development

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CNOT3 C-terminal domain is necessary for the maintenance of the pluripotent state

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CNOT3 promotes differentiation gene mRNA deadenylation and degradation

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mRNA poly(A) tail regulation plays a critical role in pluripotency

Past Roadblocks and New Opportunities in Transcription Factor Network Mapping

One of the principal mechanisms by which cells differentiate and respond to changes in external signals or conditions is by changing the activity levels of transcription factors (TFs). This changes the transcription rates of target genes via the cell's TF network, which ultimately contributes to reconfiguring cellular state. Since microarrays provided our first window into global cellular state, computational biologists have eagerly attacked the problem of mapping TF networks, a key part of the cell's control circuitry. In retrospect, however, steady-state mRNA abundance levels were a poor substitute for TF activity levels and gene transcription rates. Likewise, mapping TF binding through chromatin immunoprecipitation proved less predictive of functional regulation and less amenable to systematic elucidation of complete networks than originally hoped. This review explains these roadblocks and the current, unprecedented blossoming of new experimental techniques built on second-generation sequencing, which hold out the promise of rapid progress in TF network mapping.

Forced expression of Hnf4a induces hepatic gene activation through directed differentiation

Embryonic stem (ES) cells are capable of unlimited self-renewal and have a diverse differentiation potential. These unique features make ES cells as an attractive source for developmental biology studies. Having the mature hepatocyte in the lab with functional activities is valuable in drug discovery studies. Overexpression of hepatocyte lineage-specific transcription factors (TFs) becomes a promising approach in pluripotent cell differentiation toward liver cells. Many studies generate transgenic ES cell lines to examine the effects of specific TFs overexpression in cell differentiation. In the present report, we have addressed whether a suspension or adherent model of differentiation is an appropriate way to study the role of Hnf4a overexpression. We generated ES cells that carried a doxycycline (Dox)-inducible Hnf4a using lentiviral vectors. The transduced cells were subjected to induced Hnf4a overexpression through both spontaneous and directed differentiation methods. Gene expression analysis showed substantially increased expression of hepatic gene markers, particularly Ttr and endogenous Hnf4a, in transduced cells differentiated by the directed approach. These results demonstrated that forced expression of TFs during directed differentiation would be an appropriate way to study relevant gene activation and the effects of overexpression in the context of hepatic differentiation.

Induction of specific neuron types by overexpression of single transcription factors

Specific neuronal types derived from embryonic stem cells (ESCs) can facilitate mechanistic studies and potentially aid in regenerative medicine. Existing induction methods, however, mostly rely on the effects of the combined action of multiple added growth factors, which generally tend to result in mixed populations of neurons. Here, we report that overexpression of specific transcription factors (TFs) in ESCs can rather guide the differentiation of ESCs towards specific neuron lineages. Analysis of data on gene expression changes 2 d after induction of each of 185 TFs implicated candidate TFs for further ESC differentiation studies. Induction of 23 TFs (out of 49 TFs tested) for 6 d facilitated neural differentiation of ESCs as inferred from increased proportion of cells with neural progenitor marker PSA-NCAM. We identified early activation of the Notch signaling pathway as a common feature of most potent inducers of neural differentiation. The majority of neuron-like cells generated by induction of Ascl1, Smad7, Nr2f1, Dlx2, Dlx4, Nr2f2, Barhl2, and Lhx1 were GABA-positive and expressed other markers of GABAergic neurons. In the same way, we identified Lmx1a and Nr4a2 as inducers for neurons bearing dopaminergic markers and Isl1, Fezf2, and St18 for cholinergic motor neurons. A time-course experiment with induction of Ascl1 showed early upregulation of most neural-specific messenger RNA (mRNA) and microRNAs (miRNAs). Sets of Ascl1-induced mRNAs and miRNAs were enriched in Ascl1 targets. In further studies, enrichment of cells obtained with the induction of Ascl1, Smad7, and Nr2f1 using microbeads resulted in essentially pure population of neuron-like cells with expression profiles similar to neural tissues and expressed markers of GABAergic neurons. In summary, this study indicates that induction of transcription factors is a promising approach to generate cultures that show the transcription profiles characteristic of specific neural cell types.

Generation and gene expression profiling of 48 transcription-factor-inducible mouse embryonic stem cell lines

Mouse embryonic stem cells (ESCs) can differentiate into a wide range – and possibly all cell types in vitro, and thus provide an ideal platform to study systematically the action of transcription factors (TFs) in cell differentiation. Previously, we have generated and analyzed 137 TF-inducible mouse ESC lines. As an extension of this “NIA Mouse ESC Bank,” we generated and characterized 48 additional mouse ESC lines, in which single TFs in each line could be induced in a doxycycline-controllable manner. Together, with the previous ESC lines, the bank now comprises 185 TF-manipulable ESC lines (>10% of all mouse TFs). Global gene expression (transcriptome) profiling revealed that the induction of individual TFs in mouse ESCs for 48 hours shifts their transcriptomes toward specific differentiation fates (e.g., neural lineages by Myt1 Isl1, and St18; mesodermal lineages by Pitx1, Pitx2, Barhl2, and Lmx1a; white blood cells by Myb, Etv2, and Tbx6, and ovary by Pitx1, Pitx2, and Dmrtc2). These data also provide and lists of inferred target genes of each TF and possible functions of these TFs. The results demonstrate the utility of mouse ESC lines and their transcriptome data for understanding the mechanism of cell differentiation and the function of TFs.

Weighted enrichment method for prediction of transcription regulators from transcriptome and global chromatin immunoprecipitation data

Predicting responsible transcription regulators on the basis of transcriptome data is one of the most promising computational approaches to understanding cellular processes and characteristics. Here, we present a novel method employing vast amounts of chromatin immunoprecipitation (ChIP) experimental data to address this issue. Global high-throughput ChIP data was collected to construct a comprehensive database, containing 8 578 738 binding interactions of 454 transcription regulators. To incorporate information about heterogeneous frequencies of transcription factor (TF)-binding events, we developed a flexible framework for gene set analysis employing the weighted t-test procedure, namely weighted parametric gene set analysis (wPGSA). Using transcriptome data as an input, wPGSA predicts the activities of transcription regulators responsible for observed gene expression. Validation of wPGSA with published transcriptome data, including that from over-expressed TFs, showed that the method can predict activities of various TFs, regardless of cell type and conditions, with results totally consistent with biological observations. We also applied wPGSA to other published transcriptome data and identified potential key regulators of cell reprogramming and influenza virus pathogenesis, generating compelling hypotheses regarding underlying regulatory mechanisms. This flexible framework will contribute to uncovering the dynamic and robust architectures of biological regulation, by incorporating high-throughput experimental data in the form of weights.

Identifying gene expression modules that define human cell fates

Using a compendium of cell-state-specific gene expression data, we identified genes that uniquely define cell states, including those thought to represent various developmental stages. Our analysis sheds light on human cell fate through the identification of core genes that are altered over several developmental milestones, and across regional specification. Here we present cell-type specific gene expression data for 17 distinct cell states and demonstrate that these modules of genes can in fact define cell fate. Lastly, we introduce a web-based database to disseminate the results.

Systematic identification of gene family regulators in mouse and human embryonic stem cells

Pluripotent self-renewing embryonic stem cells (ESCs) have been the focus of a growing number of high-throughput experiments, revealing the genome-wide locations of hundreds of transcription factors and histone modifications. While most of these datasets were used in a specific context, all datasets combined offer a comprehensive view of chromatin characteristics and regulatory elements that govern cell states. Here, using hundreds of datasets in ESCs, we generated colocalization maps of chromatin proteins and modifications, and built a discovery pipeline for regulatory proteins of gene families. By comparing genome-wide binding data with over-expression and knockdown analysis of hundreds of genes, we discovered that the pluripotency-related factor NR5A2 separates mitochondrial from cytosolic ribosomal genes, regulating their expression. We further show that genes with a common chromatin profile are enriched for distinct Gene Ontology (GO) categories. Our approach can be generalized to reveal common regulators of any gene group; discover novel gene families, and identify common genomic elements based on shared chromatin features.

Genome-wide mapping of promoter-anchored interactions with close to single-enhancer resolution

Although the locations of promoters and enhancers have been identified in several cell types, we still have limited information on their connectivity. We developed HiCap, which combines a 4-cutter restriction enzyme Hi-C with sequence capture of promoter regions. Applying the method to mouse embryonic stem cells, we identified promoter-anchored interactions involving 15,905 promoters and 71,984 distal regions. The distal regions were enriched for enhancer marks and transcription, and had a mean fragment size of only 699 bp — close to single-enhancer resolution. High-resolution maps of promoter-anchored interactions with HiCap will be important for detailed characterizations of chromatin interaction landscapes.

ExAtlas: An interactive online tool for meta-analysis of gene expression data

We have developed ExAtlas, an on-line software tool for meta-analysis and visualization of gene expression data. In contrast to existing software tools, ExAtlas compares multi-component data sets and generates results for all combinations (e.g. all gene expression profiles versus all Gene Ontology annotations). ExAtlas handles both users' own data and data extracted semi-automatically from the public repository (GEO/NCBI database). ExAtlas provides a variety of tools for meta-analyses: (1) standard meta-analysis (fixed effects, random effects, z-score, and Fisher's methods); (2) analyses of global correlations between gene expression data sets; (3) gene set enrichment; (4) gene set overlap; (5) gene association by expression profile; (6) gene specificity; and (7) statistical analysis (ANOVA, pairwise comparison, and PCA). ExAtlas produces graphical outputs, including heatmaps, scatter-plots, bar-charts, and three-dimensional images. Some of the most widely used public data sets (e.g. GNF/BioGPS, Gene Ontology, KEGG, GAD phenotypes, BrainScan, ENCODE ChIP-seq, and protein-protein interaction) are pre-loaded and can be used for functional annotations.

Transcription factor AP-2γ induces early Cdx2 expression and represses HIPPO signaling to specify the trophectoderm lineage

Cell fate decisions are fundamental to the development of multicellular organisms. In mammals the first cell fate decision involves segregation of the pluripotent inner cell mass and the trophectoderm, a process regulated by cell polarity proteins, HIPPO signaling and lineage-specific transcription factors such as CDX2. However, the regulatory mechanisms that operate upstream to specify the trophectoderm lineage have not been established. Here we report that transcription factor AP-2γ (TFAP2C) functions as a novel upstream regulator of Cdx2 expression and position-dependent HIPPO signaling in mice. Loss- and gain-of-function studies and promoter analysis revealed that TFAP2C binding to an intronic enhancer is required for activation of Cdx2 expression during early development. During the 8-cell to morula transition TFAP2C potentiates cell polarity to suppress HIPPO signaling in the outside blastomeres. TFAP2C depletion triggered downregulation of PARD6B, loss of apical cell polarity, disorganization of F-actin, and activation of HIPPO signaling in the outside blastomeres. Rescue experiments using Pard6b mRNA restored cell polarity but only partially corrected position-dependent HIPPO signaling, suggesting that TFAP2C negatively regulates HIPPO signaling via multiple pathways. Several genes involved in regulation of the actin cytoskeleton (including Rock1, Rock2) were downregulated in TFAP2C-depleted embryos. Inhibition of ROCK1 and ROCK2 activity during the 8-cell to morula transition phenocopied TFAP2C knockdown, triggering a loss of position-dependent HIPPO signaling and decrease in Cdx2 expression. Altogether, these results demonstrate that TFAP2C facilitates trophectoderm lineage specification by functioning as a key regulator of Cdx2 transcription, cell polarity and position-dependent HIPPO signaling.

Inferring dynamic gene regulatory networks in cardiac differentiation through the integration of multi-dimensional data

Background

Decoding the temporal control of gene expression patterns is key to the understanding of the complex mechanisms that govern developmental decisions during heart development. High-throughput methods have been employed to systematically study the dynamic and coordinated nature of cardiac differentiation at the global level with multiple dimensions. Therefore, there is a pressing need to develop a systems approach to integrate these data from individual studies and infer the dynamic regulatory networks in an unbiased fashion.

Results

We developed a two-step strategy to integrate data from (1) temporal RNA-seq, (2) temporal histone modification ChIP-seq, (3) transcription factor (TF) ChIP-seq and (4) gene perturbation experiments to reconstruct the dynamic network during heart development. First, we trained a logistic regression model to predict the probability (LR score) of any base being bound by 543 TFs with known positional weight matrices. Second, four dimensions of data were combined using a time-varying dynamic Bayesian network model to infer the dynamic networks at four developmental stages in the mouse [mouse embryonic stem cells (ESCs), mesoderm (MES), cardiac progenitors (CP) and cardiomyocytes (CM)]. Our method not only infers the time-varying networks between different stages of heart development, but it also identifies the TF binding sites associated with promoter or enhancers of downstream genes.

The LR scores of experimentally verified ESCs and heart enhancers were significantly higher than random regions (p <10⁻¹⁰⁰), suggesting that a high LR score is a reliable indicator for functional TF binding sites. Our network inference model identified a region with an elevated LR score approximately −9400 bp upstream of the transcriptional start site of Nkx2-5, which overlapped with a previously reported enhancer region (−9435 to −8922 bp). TFs such as Tead1, Gata4, Msx2, and Tgif1 were predicted to bind to this region and participate in the regulation of Nkx2-5 gene expression. Our model also predicted the key regulatory networks for the ESC-MES, MES-CP and CP-CM transitions.

Conclusion

We report a novel method to systematically integrate multi-dimensional -omics data and reconstruct the gene regulatory networks. This method will allow one to rapidly determine the cis-modules that regulate key genes during cardiac differentiation.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-015-0460-0) contains supplementary material, which is available to authorized users.

SOX9 accelerates ESC differentiation to three germ layer lineages by repressing SOX2 expression through P21 (WAF1/CIP1)

Upon removal of culture conditions that maintain an undifferentiated state, mouse embryonic stem cells (ESCs) differentiate into various cell types. Differentiation can be facilitated by forced expression of certain transcription factors (TFs), each of which can generally specify a particular developmental lineage. We previously established 137 mouse ESC lines, each of which carried a doxycycline-controllable TF. Among them, Sox9 has unique capacity: its forced expression accelerates differentiation of mouse ESCs into cells of all three germ layers. With the additional use of specific culture conditions, overexpression of Sox9 facilitated the generation of endothelial cells, hepatocytes and neurons from ESCs. Furthermore, Sox9 action increases formation of p21 (WAF1/CIP1), which then binds to the SRR2 enhancer of pluripotency marker Sox2 and inhibits its expression. Knockdown of p21 abolishes inhibition of Sox2 and Sox9-accelerated differentiation, and reduction of Sox2 2 days after the beginning of ESC differentiation can comparably accelerate mouse ESC formation of cells of three germ layers. These data implicate the involvement of the p21-Sox2 pathway in the mechanism of accelerated ESC differentiation by Sox9 overexpression. The molecular cascade could be among the first steps to program ESC differentiation.

CellNet: network biology applied to stem cell engineering

Somatic cell reprogramming, directed differentiation of pluripotent stem cells, and direct conversions between differentiated cell lineages represent powerful approaches to engineer cells for research and regenerative medicine. We have developed CellNet, a network biology platform that more accurately assesses the fidelity of cellular engineering than existing methodologies and generates hypotheses for improving cell derivations. Analyzing expression data from 56 published reports, we found that cells derived via directed differentiation more closely resemble their in vivo counterparts than products of direct conversion, as reflected by the establishment of target cell-type gene regulatory networks (GRNs). Furthermore, we discovered that directly converted cells fail to adequately silence expression programs of the starting population and that the establishment of unintended GRNs is common to virtually every cellular engineering paradigm. CellNet provides a platform for quantifying how closely engineered cell populations resemble their target cell type and a rational strategy to guide enhanced cellular engineering.

Chromatin properties of regulatory DNA probed by manipulation of transcription factors

Transcription factors (TFs) bind to DNA and regulate the transcription of nearby genes. However, only a small fraction of TF binding sites have such regulatory effects. Here we search for the predictors of functional binding sites by carrying out a systematic computational screening of a variety of contextual factors (histone modifications, nuclear lamin-bindings, and cofactor bindings). We used regression analysis to test if contextual factors are associated with upregulation or downregulation of neighboring genes following the induction or knockdown of the 9 TFs in mouse embryonic stem (ES) cells. Functional TF binding sites appeared to be either active (i.e., bound by P300, CHD7, mediator, cohesin, and SWI/SNF) or repressed (i.e., with H3K27me3 histone marks and bound by Polycomb factors). Active binding sites mediated the downregulation of nearby genes upon knocking down the activating TFs or inducing repressors. Repressed TF binding sites mediated the upregulation of nearby genes (e.g., poised developmental regulators) upon inducing TFs. In addition, repressed binding sites mediated repressive effects of TFs, identified by the downregulation of target genes after the induction of TFs or by the upregulation of target genes after the knockdown of TFs. The contextual factors associated with functions of DNA-bound TFs were used to improve the identification of candidate target genes regulated by TFs.

Identification of transcription factors for lineage-specific ESC differentiation

A network of transcription factors (TFs) determines cell identity, but identity can be altered by overexpressing a combination of TFs. However, choosing and verifying combinations of TFs for specific cell differentiation have been daunting due to the large number of possible combinations of ∼2,000 TFs. Here, we report the identification of individual TFs for lineage-specific cell differentiation based on the correlation matrix of global gene expression profiles. The overexpression of identified TFs—Myod1, Mef2c, Esx1, Foxa1, Hnf4a, Gata2, Gata3, Myc, Elf5, Irf2, Elf1, Sfpi1, Ets1, Smad7, Nr2f1, Sox11, Dmrt1, Sox9, Foxg1, Sox2, or Ascl1—can direct efficient, specific, and rapid differentiation into myocytes, hepatocytes, blood cells, and neurons. Furthermore, transfection of synthetic mRNAs of TFs generates their appropriate target cells. These results demonstrate both the utility of this approach to identify potent TFs for cell differentiation, and the unanticipated capacity of single TFs directly guides differentiation to specific lineage fates.

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Lineage-determining single TFs are identified based on the correlation matrix

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A proof of concept is demonstrated for ESC differentiation by 21 TFs

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TFs orchestrate global gene expression changes via direct binding to target genes

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Transfections of synthetic TF mRNAs generate desired differentiated cells

Identification of the missing pluripotency mediator downstream of leukaemia inhibitory factor

Self-renewal of pluripotent mouse embryonic stem (ES) cells is sustained by the cytokine leukaemia inhibitory factor (LIF) acting through the transcription factor Stat3. Several targets of Stat3 have previously been identified, most notably the reprogramming factor Klf4. However, such factors are neither required nor sufficient for the potent effect of LIF. We took advantage of Stat3 null ES cells to confirm that Stat3 mediates the self-renewal response to LIF. Through comparative transcriptome analysis intersected with genome location data, we arrived at a set of candidate transcription factor effectors. Among these, Tfcp2l1 (also known as Crtr-1) was most abundant. Constitutive expression of Tfcp2l1 at levels similar to those induced by LIF effectively substituted for LIF or Stat3 in sustaining clonal self-renewal and pluripotency. Conversely, knockdown of Tfcp2l1 profoundly compromised responsiveness to LIF. We further found that Tfcp2l1 is both necessary and sufficient to direct molecular reprogramming of post-implantation epiblast stem cells to naïve pluripotency. These results establish Tfcp2l1 as the principal bridge between LIF/Stat3 input and the transcription factor core of naïve pluripotency.

Systematic repression of transcription factors reveals limited patterns of gene expression changes in ES cells

Networks of transcription factors (TFs) are thought to determine and maintain the identity of cells. Here we systematically repressed each of 100 TFs with shRNA and carried out global gene expression profiling in mouse embryonic stem (ES) cells. Unexpectedly, only the repression of a handful of TFs significantly affected transcriptomes, which changed in two directions/trajectories: one trajectory by the repression of either Pou5f1 or Sox2; the other trajectory by the repression of either Esrrb, Sall4, Nanog, or Tcfap4. The data suggest that the trajectories of gene expression change are already preconfigured by the gene regulatory network and roughly correspond to extraembryonic and embryonic fates of cell differentiation, respectively. These data also indicate the robustness of the pluripotency gene network, as the transient repression of most TFs did not alter the transcriptomes.